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Author: Santhosh Kumar Balan
Publisher: BoD – Books on Demand
ISBN: 1839687983
Category : Computers
Languages : en
Pages : 154
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Book Description
Data integrity is the quality, reliability, trustworthiness, and completeness of a data set, providing accuracy, consistency, and context. Data quality refers to the state of qualitative or quantitative pieces of information. Over five sections, this book discusses data integrity and data quality as well as their applications in various fields.
Author: Santhosh Kumar Balan
Publisher: BoD – Books on Demand
ISBN: 1839687983
Category : Computers
Languages : en
Pages : 154
Get Book Here
Book Description
Data integrity is the quality, reliability, trustworthiness, and completeness of a data set, providing accuracy, consistency, and context. Data quality refers to the state of qualitative or quantitative pieces of information. Over five sections, this book discusses data integrity and data quality as well as their applications in various fields.
Author: R. D. McDowall
Publisher: Royal Society of Chemistry
ISBN: 178801281X
Category : Computers
Languages : en
Pages : 660
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Book Description
This book provides practical and detailed advice on how to implement data governance and data integrity for regulated analytical laboratories working in the pharmaceutical and allied industries.
Author: Niall Richard Murphy
Publisher: "O'Reilly Media, Inc."
ISBN: 1491951176
Category :
Languages : en
Pages : 552
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Book Description
The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems? In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization. This book is divided into four sections: Introduction—Learn what site reliability engineering is and why it differs from conventional IT industry practices Principles—Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE) Practices—Understand the theory and practice of an SRE’s day-to-day work: building and operating large distributed computing systems Management—Explore Google's best practices for training, communication, and meetings that your organization can use
Author: José Rodríguez-Pérez
Publisher: Quality Press
ISBN: 0873899873
Category : Business & Economics
Languages : en
Pages : 137
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Book Description
Data integrity is a global mandatory requirement for the regulated healthcare industry. It is more than a mere expectationits a basic element of good documentation practices, one of the most fundamental pillars of a quality management system. Robustness and accuracy of the data submitted by manufacturers to regulatory authorities when bringing a medical product to market are crucial. The purpose of this book is to consolidate existing data integrity principles and expectations from several regulatory sourcesincluding the U.S. Food and Drug Administration, World Health Organization, and European Medicines Agencyinto a single and handy document that provides detailed, illustrative implementation guidance. It serves as a means of understanding regulatory agencies position on good data management and the minimum expectation for how medical product manufacturers can achieve compliance.
Author: Danette McGilvray
Publisher: Academic Press
ISBN: 0128180161
Category : Computers
Languages : en
Pages : 378
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Book Description
Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. - Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach - Contains real examples from around the world, gleaned from the author's consulting practice and from those who implemented based on her training courses and the earlier edition of the book - Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices - A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309172802
Category : Medical
Languages : en
Pages : 88
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Book Description
In an effort to increase knowledge and understanding of the process of assuring data quality and validity in clinical trials, the IOM hosted a workshop to open a dialogue on the process to identify and discuss issues of mutual concern among industry, regulators, payers, and consumers. The presenters and panelists together developed strategies that could be used to address the issues that were identified. This IOM report of the workshop summarizes the present status and highlights possible strategies for making improvements to the education of interested and affected parties as well as facilitating future planning.
Author: Robert S. DiStefano
Publisher:
ISBN: 9780831134228
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
Asset data integrity is a critical aspect of every business, yet it is often overlooked. This book will not only provide an appreciation of this fact, it will also provide a road map to achieving value out of something most CEOs, managers, and workers often overlook. The authors bring many years of experience and hands-on expertise that cannot be obtained elsewhere. An assessment tool is provided so once the problem is recognized by the reader, areas of improvement can be easily recognized. A detailed appendix provides further clarity.
Author: Institute of Medicine
Publisher: National Academies Press
ISBN: 0309147824
Category : Computers
Languages : en
Pages : 179
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Book Description
As digital technologies are expanding the power and reach of research, they are also raising complex issues. These include complications in ensuring the validity of research data; standards that do not keep pace with the high rate of innovation; restrictions on data sharing that reduce the ability of researchers to verify results and build on previous research; and huge increases in the amount of data being generated, creating severe challenges in preserving that data for long-term use. Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age examines the consequences of the changes affecting research data with respect to three issues - integrity, accessibility, and stewardship-and finds a need for a new approach to the design and the management of research projects. The report recommends that all researchers receive appropriate training in the management of research data, and calls on researchers to make all research data, methods, and other information underlying results publicly accessible in a timely manner. The book also sees the stewardship of research data as a critical long-term task for the research enterprise and its stakeholders. Individual researchers, research institutions, research sponsors, professional societies, and journals involved in scientific, engineering, and medical research will find this book an essential guide to the principles affecting research data in the digital age.
Author: Agency for Healthcare Research and Quality/AHRQ
Publisher: Government Printing Office
ISBN: 1587634333
Category : Medical
Languages : en
Pages : 385
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Book Description
This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews.
Author: Gerhard Svolba
Publisher: SAS Institute
ISBN: 1612902278
Category : Computers
Languages : en
Pages : 356
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Book Description
Analytics offers many capabilities and options to measure and improve data quality, and SAS is perfectly suited to these tasks. Gerhard Svolba's Data Quality for Analytics Using SAS focuses on selecting the right data sources and ensuring data quantity, relevancy, and completeness. The book is made up of three parts. The first part, which is conceptual, defines data quality and contains text, definitions, explanations, and examples. The second part shows how the data quality status can be profiled and the ways that data quality can be improved with analytical methods. The final part details the consequences of poor data quality for predictive modeling and time series forecasting. With this book you will learn how you can use SAS to perform advanced profiling of data quality status and how SAS can help improve your data quality. This book is part of the SAS Press program.
